Graph contrastive learning (GCL) has attracted extensive research interest due to its powerful ability to capture latent structural and semantic information of graphs in a self-supervised manner. Existing GCL methods commonly adopt predefined graph augmentations to generate two contrastive views. Subsequently. they design a contrastive pretext task between these views with the goal of... https://www.johnsmustangs.shop/product-category/1964-1973-fuel-system/